iGEMS: an integrated model for identification of alternative exon usage events

iGEMS:用于识别替代外显子使用事件的集成模型

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作者:Sanjana Sood, Krzysztof J Szkop, Asif Nakhuda, Iain J Gallagher, Carl Murie, Robert J Brogan, Jaakko Kaprio, Heikki Kainulainen, Philip J Atherton, Urho M Kujala, Thomas Gustafsson, Ola Larsson, James A Timmons1

Abstract

DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with (n = 9) or without (n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (∼90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3'UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5-10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.

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